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Identification of behavior patterns in household solid waste generation in Mexicali's city: Study case

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  • Márquez, Ma. Ysabel
  • Ojeda, Sara
  • Hidalgo, Hugo

Abstract

A strategy of household waste data analysis is proposed in this work, based on the WEKA workbench, developed on the Pattern Recognition community. The analysis was conducted on data collected from homes at residential areas in the city of Mexicali, México. The data included information about solid waste produced and also the householder's commitment to the environment, assessed in a Likert's scale based on a questionnaire. A cluster analysis and a tree classifier constructed using the clustered data are presented. An analysis of the decision tree allowed to translate the resulting tree in a set of production rules. After the interpretation of these rules, we were able to predict an environmental behavior, based on the information about waste generation and the questionnaire answers. The rules showed a tendency to bring together members of the same family, concurring in all cases the reference to the same period of waste generation. The elements identified on each rule indicate that the socioeconomic stratum is an important factor, related to behavioral attributes and consumption habits, the main relationship is based on attributes of waste generation as glass, organics, paper, inert, mixer containers and sanitary. The discovered relationships between the cluster, socio-demographic, behavioral and waste attributes are presented and discussed.

Suggested Citation

  • Márquez, Ma. Ysabel & Ojeda, Sara & Hidalgo, Hugo, 2008. "Identification of behavior patterns in household solid waste generation in Mexicali's city: Study case," Resources, Conservation & Recycling, Elsevier, vol. 52(11), pages 1299-1306.
    • Handle: RePEc:eee:recore:v:52:y:2008:i:11:p:1299-1306
    DOI: 10.1016/j.resconrec.2008.07.011
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    References listed on IDEAS

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    1. Bruno S. Frey & Alois Stutzer, 2006. "Environmental Morale and Motivation," IEW - Working Papers 288, Institute for Empirical Research in Economics - University of Zurich.
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    1. Gi-Wook Cha & Won-Hwa Hong & Young-Chan Kim, 2023. "Performance Improvement of Machine Learning Model Using Autoencoder to Predict Demolition Waste Generation Rate," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    2. Jones, N. & Evangelinos, K. & Halvadakis, C.P. & Iosifides, T. & Sophoulis, C.M., 2010. "Social factors influencing perceptions and willingness to pay for a market-based policy aiming on solid waste management," Resources, Conservation & Recycling, Elsevier, vol. 54(9), pages 533-540.
    3. Decai Tang & Lei Shi & Xiaojuan Huang & Ziqian Zhao & Biao Zhou & Brandon J. Bethel, 2022. "Influencing Factors on the Household-Waste-Classification Behavior of Urban Residents: A Case Study in Shanghai," IJERPH, MDPI, vol. 19(11), pages 1-16, May.
    4. Jürgen Dunkel & David Dominguez & Óscar G. Borzdynski & Ángel Sánchez, 2022. "Solid Waste Analysis Using Open-Access Socio-Economic Data," Sustainability, MDPI, vol. 14(3), pages 1-24, January.

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